Abstract
Dietary assessment traditionally relies on self-reported data, which are often inaccurate and may result in erroneous diet-disease risk associations. We illustrate how urinary metabolic phenotyping can be used as an alternative approach to obtain information on dietary patterns. We used two multipass 24 h dietary recalls, obtained on two occasions on average 3 weeks apart, paired with two 24 h urine collections from 1,848 US individuals; 67 nutrients influenced the urinary metabotype (metabolic phenotype) of 46 structurally identified metabolites characterized by H-1 NMR spectroscopy. We investigated the stability of each metabolite over time and showed that the urinary metabolic profile is more stable within individuals than reported dietary patterns. The 46 metabolites accurately predicted healthy and unhealthy dietary patterns in a free-living US cohort, and these predictions were replicated in an independent UK cohort. We mapped these metabolites into a host-microbial metabolic network to identify key pathways and functions related to diet. These data can be used in future studies to evaluate how this set of diet-derived, stable, measurable bioanalytical markers is associated with disease risk. This knowledge may give new insights into biological pathways that characterize the shift from a healthy to an unhealthy metabolic phenotype and hence indicate entry points for prevention and intervention strategies.
Urinary metabolic phenotyping of 1,848 adults in the United States shows that 46 structurally identified metabolites were influenced by intakes of 67 nutrients, and accurately predicted healthy and unhealthy dietary patterns. These urinary biomarkers are diet-derived, stable, measurable and associated with disease risk, thereby representing an advance on traditional ways of obtaining information about dietary patterns.